Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Publisher: American Society of Tropical Medicine and Hygiene
Languages: English
Types: Article
This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidential interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. UNICEF/WHO, 2015. Progress on Sanitation and DrinkingWater: 2015 Update and MDG Assessment. World Health Organization and UNICEF, Geneva, Switzerland.
    • 2. King JD, Endeshaw T, Escher E, Alemtaye G, Melaku S, Gelaye W, Worku A, Adugna M, Melak B, Teferi T, Zerihun M, Gesese D, Tadesse Z, Mosher AW, Odermatt P, Utzinger J, Marti H, Ngondi J, Hopkins DR, Emerson PM, 2013. Intestinal parasite prevalence in an area of Ethiopia after implementing the SAFE strategy, enhanced outreach services, and health extension program. PLoS Negl Trop Dis 7: e2223.
    • 3. Ross RK, King JD, Damte M, Ayalew F, Gebre T, Cromwell EA, Teferi T, Emerson PM, 2011. Evaluation of household latrine coverage in Kewot woreda, Ethiopia, 3 years after implementing interventions to control blinding trachoma. Int Health 3: 251-258.
    • 4. O'Loughlin R, Fentie G, Flannery B, Emerson PM, 2006. Follow-up of a low cost latrine promotion programme in one district of Amhara, Ethiopia: characteristics of early adopters and non-adopters. Trop Med Int Health 11: 1406-1415.
    • 5. Kar K, Chambers R, 2008. Handbook on Community-Led Total Sanitation. London, United Kingdom: Plan UK.
    • 6. Faris K, Rosenbaum J, 2011. Learning by Doing: Working at Scale in Ethiopia. Washington, DC: Water and Sanitation Program, World Bank.
    • 7. Banteyerga H, 2011. Ethiopia's health extension program: improving health through community involvement. MEDICC Rev 13: 46-49.
    • 8. Wagner EG, Lanoix JN, 1958. Excreta Disposal for Rural Areas and Small Communities. WHO Monograph Series. Geneva, Switzerland: World Health Organization.
    • 9. Dreibelbis R, Winch PJ, Leontsini E, Hulland KR, Ram PK, Unicomb L, Luby SP, 2013. The integrated behavioural model for water, sanitation, and hygiene: a systematic review of behavioural models and a framework for designing and evaluating behaviour change interventions in infrastructure-restricted settings. BMC Public Health 13: 1015.
    • 10. O'Connell K, 2014. What Influences Open Defecation and Latrine Ownership in Rural Households?: Findings from a Global Review. Washington, DC: Water and Sanitation Program, World Bank.
    • 11. Jackson B, 2004. Sanitation and Hygiene in Kenya: Lessons on What Drives Demand for Improved Sanitation. Washington, DC: Water and Sanitation Program, The World Bank.
    • 12. Jenkins MW, Scott B, 2007. Behavioral indicators of household decision-making and demand for sanitation and potential gains from social marketing in Ghana. Soc Sci Med 64: 2427-2442.
    • 13. Sara S, Graham J, 2014. Ending open defecation in rural Tanzania: which factors facilitate latrine adoption? Int J Environ Res Public Health 11: 9854-9870.
    • 14. Jenkins MW, Sugden S, 2006. Rethinking Sanitation: Lessons and Innovation for Sustainability and Success in the New Millennium. Human Development Report 2006. New York, NY: Human Development Report Office, UNDP.
    • 15. Jenkins MW, Curtis V, 2005. Achieving the 'good life': why some people want latrines in rural Benin. Soc Sci Med 61: 2446-2459.
    • 16. Simms VM, Makalo P, Bailey RL, Emerson PM, 2005. Sustainability and acceptability of latrine provision in The Gambia. Trans R Soc Trop Med Hyg 99: 631-637.
    • 17. Jenkins MW, Cairncross S, 2010. Modelling latrine diffusion in Benin: towards a community typology of demand for improved sanitation in developing countries. J Water Health 8: 166-183.
    • 18. Bewket W, Conway D, 2007. A note on the temporal and spatial variability of rainfall in the drought-prone Amhara region of Ethiopia. Int J Climatol 27: 1467-1477.
    • 19. European Commission JRC, 2003. Global Land Cover 2000 Database. Available at: http://forobs.jrc.ec.europa.eu/products/ glc2000/glc2000.php. Accessed July 9, 2016.
    • 20. Central Statistical Agency (CSA), 2007. 2007 Population and Housing Census of Ethiopia. Addis Ababa, Ethiopia: Central Statistical Agency.
    • 21. Turner AG, Magnani RJ, Shuaib M, 1996. A not quite as quick but much cleaner alternative to the Expanded Programme on Immunization (EPI) Cluster Survey design. Int J Epidemiol 25: 198-203.
    • 22. UNICEF, 2006. Monitoring the Situation of Children and Women. Multiple Indicator Cluster Survey Manual 2005. New York, NY: UNICEF.
    • 23. King JD, Buolamwini J, Cromwell EA, Panfel A, Teferi T, Zerihun M, Melak B, Watson J, Tadesse Z, Vienneau D, Ngondi J, Utzinger J, Odermatt P, Emerson PM, 2013. A novel electronic data collection system for large-scale surveys of neglected tropical diseases. PLoS One 8: e74570.
    • 24. FAO/IIASA/ISRIC/ISS-CAS/JRC, 2012. Harmonized World Soil Database. Available at: http://webarchive.iiasa.ac.at/Research/ LUC/External-World-soil-database/HTML/index.html?sb=1. Accessed February 10, 2015.
    • 25. FAO, 2007. Digital Soil Map of the World. Rome, Italy: Food and Agriculture Organization of the United Nations.
    • 26. USGS, 2009. Africa Ecosystems Mapping Project. Available at: http:// rmgsc.cr.usgs.gov/outgoing/ecosystems/AfricaData/. Accessed February 27, 2015.
    • 27. Cress JJ, Sayre R, Comer P, Warner H, 2009. Topographic Moisture Potential of the Conterminous United States: U.S. Geological Survey Scientific Investigations Map 3086, Scale 1:5,000,000. Available at: http://pubs.usgs.gov/sim/3086/. Accessed February 27, 2015.
    • 28. Jarvis A, Reuter HI, Nelson A, Guevara E, 2008. Hole-filled SRTM for the Globe Version 4. Available at: http://www.divagis.org. Accessed February 10, 2015.
    • 29. AfSIS, 2011. Annual Normalized Difference Vegetation Index. Available at: ftp://africagrids.net/250m/MOD13Q1/NDVI. Accessed February 4, 2015.
    • 30. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A, 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25: 1965-1978.
    • 31. Center for International Earth Science Information Network (CIESIN) Columbia University, Information Technology Outreach Services (ITOS), University of Georgia, 2013. Global Roads Open Access Data Set, Version 1 (gROADSv1). Available at: http://dx.doi.org/10.7927/H4VD6WCT. Accessed January 20, 2015.
    • 32. Bright EA, Coleman PR, Rose AN, Urban ML, 2012. LandScan 2011. Available at: http://www.ornl.gov/landscan/. Accessed April 17, 2015.
    • 33. Kleinbaum DG, Klein M, 2010. Logistic Regression: A SelfLearning Text, 3rd edition. New York, NY: Springer.
    • 34. Vazquez-Prokopec GM, Spillmann C, Zaidenberg M, Gurtler RE, Kitron U, 2012. Spatial heterogeneity and risk maps of community infestation by Triatoma infestans in rural northwestern Argentina. PLoS Negl Trop Dis 6: e1788.
    • 35. Burnham KP, Anderson DR, 2002. Model Selection and Multimodal Inference: A Practical Information-Theoretic Approach. New York, NY: Springer.
    • 36. Rosenberg ES, 2014. proc_EVW.sas [Program for SAS software]. Atlanta, GA: Rollins School of Public Health, Emory University.
    • 37. Flanders WD, Tucker G, Krishnadasan A, Martin D, Honig E, McClellan WM, 1999. Validation of the pneumonia severity index. J Gen Intern Med 14: 333-340.
    • 38. Janssen KJ, Moons KG, Kalkman CJ, Grobbee DE, Vergouwe Y, 2008. Updating methods improved the performance of a clinical prediction model in new patients. J Clin Epidemiol 61: 76-86.
    • 39. Pan W, 2001. Akaike's information criterion in generalized estimating equations. Biometrics 57: 120-125.
    • 40. DeLong ER, DeLong DM, Clarke-Pearson DL, 1988. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44: 837-845.
    • 41. Johnson LK, 2004. Earth collapse of soil pits and trench excavations. Muckel GB, ed. Understanding Soil Risks and Hazards: Using Soil Survey to Identify Areas with Risks and Hazards to Human Life and Property. Lincoln, Nebraska: United States Department of Agriculture, Natural Resources Conservation Service, National Soil Survey Center.
    • 42. USDA, 1993. Soil Survey Manual. Washington, DC: Soil Survey Division Staff, U.S. Department of Agriculture.
    • 43. FAO, 1988. FAO/UNESCO Soil Map of the World, Revised Legend, with Corrections and Updates. World Soil Resources Report 60, FAO, Rome. Reprinted with updates as Technical Paper 20. Wageningen, Germany: ISRIC.
    • 44. Franceys R, Pickford J, Reed R, 1992. A Guide to the Development of On-Site Sanitation. Geneva, Switzerland: World Health Organization.
    • 45. Jenkins M, 2004. Who Buys Latrines, Where and Why? Nairobi, Kenya: Water and Sanitation Program Africa, World Bank.
    • 46. Grimason AM, Davison K, Tembo KC, Jabu GC, Jackson MH, 2000. Problems associated with the use of pit latrines in Blantyre, Republic of Malawi. J R Soc Promot Health 120: 175-182.
    • 47. FDRE/MOH, 2007. Federal Democratic Republic of Ethiopia Ministry of Health National Hygiene and Sanitation Strategy 2005. Washington, DC: Water and Sanitation Program, World Bank.
    • 48. Perez A, 2009. Interlocking Stabilised Soil Blocks: Appropriate Earth Technologies in Uganda. Nairobi, Kenya: United Nations Human Settlements Programme (UN-Habitat).
    • 49. Morshed G, Sobhan A, 2010. The search for appropriate latrine solutions for flood-prone areas of Bangladesh. Waterlines 29: 236-245.
    • 50. O'Donnell E, 2015. Plinth Performance Review. Bogra, Bangladesh: Chars Livelihood Programme.
    • 51. FDRE/MOH, 2007. Federal Democratic Republic of Ethiopia Ministry of Health National Hygiene and “On-Site” Sanitation Protocol 2006. Washington, DC: Water and Sanitation Program, World Bank.
    • 52. Pullan RL, Freeman MC, Gething PW, Brooker SJ, 2014. Geographical inequalities in use of improved drinking water supply and sanitation across sub-Saharan Africa: mapping and spatial analysis of cross-sectional survey data. PLoS Med 11: e1001626.
  • No similar publications.

Share - Bookmark

Cite this article